DBMS > GeoSpock vs. IBM Db2 vs. NCache vs. Pinecone vs. SQLite

System Properties Comparison GeoSpock vs. IBM Db2 vs. NCache vs. Pinecone vs. SQLite

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

Common in IBM host environments, 2 different versions for host and Windows/Linux

Open-Source and Enterprise in-memory Key-Value Store

A managed, cloud-native vector database

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Key-value store

Vector DBMS

Relational DBMS

Secondary database models

Time Series DBMS

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Search engine

Using distributed Lucene

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	125.90
Rank	#9	Overall
	#6	Relational DBMS

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	3.23
Rank	#92	Overall
	#2	Vector DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

geospock.com

www.ibm.com/products/db2

www.alachisoft.com/ncache

www.pinecone.io

www.sqlite.org

Technical documentation

www.ibm.com/docs/en/db2

www.alachisoft.com/resources/docs

docs.pinecone.io/docs/overview

www.sqlite.org/docs.html

Developer

GeoSpock

IBM

Alachisoft

Pinecone Systems, Inc

Dwayne Richard Hipp

Initial release

1983

host version

2005

2019

2000

Current release

2.0, September 2019

12.1, October 2016

5.3.3, April 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

free version is available

Open Source

Enterprise Edition available

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Javascript

C and C++

C#, .NET, .NET Core, Java

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
Windows

hosted

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

String, Number, Boolean

yes

not rigid because of 'dynamic typing' concept.

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

IDistributedCache
JCache
LINQ
Proprietary native API

RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

support for stored procedures with SQL-Server CLR

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

only with Windows/Unix/Linux Version

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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